Graduate Theses & Dissertations

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Application of Data Science to Paramedic Data
Paramedic data has significant potential for research. Paramedics see many patients every year and collect a wide variety of crucial data at each encounter. This data is rarely used for good reason: it’s messy and hard to work with. But like theunderdog character in a classic movie, with a little bit of work and a lot of understanding, paramedic data has significant potential to change the world of medical research. Paramedics throughout the world are involved in research every day, but most of this research uses purpose-built data structures and never takes advantage of the existing data that paramedics create as part of their everyday work. Through a project-based approach grounded in developing a better understanding of the opioid crisis, this thesis will examine the quantity and structure of the existing paramedic data, the complexities of its current design, the steps necessary to access it, and the processes necessary to clean existing data to a point where it can be easily modelled. Once we have our dataset, we will explore the challenges of choosing key metrics by examining the effectiveness of metrics currently employed to monitor the opioid crisis and the influences public health programs and changing policies have had on these metrics. Next, we will explore the temporal distributions of opioid and other intoxicant use with an eye to providing data to support public health in their harm reduction efforts. And lastly, we will look at the effect of fixed- and floating-point temporal influences on intoxicant-related calls with an eye to how these temporal points can affect call volumes. By using this exploration of the opioid crisis, this thesis will show that with a more thorough understanding of what paramedic data is, what data points are available, and the processes needed to transform it, paramedic data has the potential to greatly expand the limits of health care data science into a more precise and more all-encompassing discipline. Author Keywords: Ambulance, Data Science, Opioid, Overdose, Paramedic, Pre-hospital
Particulate Matter Component Analyses in Relation to Public Health in Canada
This thesis explores the shot-term relationship between exposure to ambient air pollution and human health through metrics such as mortality and hospitalization in Canada. We begin by detailing the organization and interpolation of air pollution data from its partially quality-controlled source form. Analyses of seasonal, regional and temporal trends of all major components of PM2.5, was performed, showing a seasonal variation across most regions and validating the dataset. A one-pollutant statistical Generalized Additive Model was applied to the data, estimating the health risk associated with exposure to thirteen different components of PM2.5. The selected components were based on those that compromised the majority of the mass and included: sulphate, nitrate, zinc, silicon, iron, nickel, vanadium, potassium, organic carbon, organic matter, elemental carbon, total carbon. Trends based on annual estimates of the association for PM2.5, and its constituents,were compared, showing that carbonaceous compounds, sulphate and nitrate had similar estimates of association. Many estimates, as is common in population ecologic epidemiology, had association estimates statistically indistinguishable from zero, but with clear features of interest, including evident differences between cold and warm season associations in Canada's temperate climate. A method to model two correlated pollutants (in this case, PM2.5 and O3) was developed using thin plate splines. In this approach, the location of the response surface (after accounting for the temperature, a smooth function of time and day of week) that corresponds to the average pollutant concentration and the average plus one unit was used as the estimate of the joint contribution of pollutants due to a unit increase. The estimates from the thin plate spline (TPS) approach were compared to the single pollutant models, with large increases and decreases in PM2.5 and O3 being captured in the TPS estimates. However, this approach indicated significantly larger error in the estimates than would be expected, indicating a possible future area for refinement. Author Keywords: Air pollution, Environmental Epidemiology, Generalized Additive Models, Human Health, Multivariate Models, Thin Plate Splines
ADHD Symptomatology Across Adulthood
Objective: To improve on several methodological issues and research gaps regarding current literature investigating the stability of ADHD symptomatology across adulthood and relationships between the two core ADHD symptom dimensions (i.e., inattention and hyperactivity-impulsivity) and multiple life outcomes in adults. Method: A large sample of postsecondary students were initially assessed for ADHD symptomatology using the Conners’ Adult ADHD Rating Scale (CAARS). Six years later, academic success was assessed using students’ official academic records (e.g., final GPAs and degree completion status), and fifteen years later, participants were re-assessed using the CAARS and several measures of life success (e.g., relationship satisfaction, career satisfaction, and stress levels). Results: Inattention and hyperactivity-impulsivity symptoms showed strong stability across the 15-year period. Additionally, greater inattention symptoms during emerging adulthood and early middle adulthood were consistently associated with poorer life success (e.g., lower GPAs, poorer relationship and career satisfaction), particularly for men. Associations for hyperactivity-impulsivity symptoms were less consistent. Conclusion: ADHD symptomatology can be conceptualized as a stable, dimensional trait across adulthood, with robust associations with measures of life success. Author Keywords: academic success, ADHD, adults, job satisfaction, relationship satisfaction, stability
Assessing factors associated with wealth and health of Ontario workers after permanent work injury
I drew on Bourdieu’s theory of capital and theorized that different forms of economic, cultural and social capital which injured workers possessed and/or acquire over their disability trajectory may affect certain outcomes of permanent impairments. Using data from a cross-sectional survey of 494 Ontario workers with permanent impairments, I measured workers’ different indicators of capital in temporal order. Hierarchical regression analyses were used to test the unique association of workers’ individual characteristics, pre-injury capital, post-injury capital, and the outcomes of permanent impairments. The results show that factors related to individual characteristics, pre-injury and post-injury capital were associated with workers’ perceived health change, whereas pre-injury and post-injury capital were most relevant factors in explaining workers’ post-injury employment status and income recovery. When looking at the significance of individual predictors, post-injury variables were most relevant in understanding the outcomes of permanent impairment. The findings suggest that many workers faced economic and health disadvantages after permanent work injury. Author Keywords: Bourdieu, hierarchical regression, theory of capital, work-related disability, workers with permanent impairments
Prescription Drugs
Medication used to treat human illness is one of the greatest developments in human history. In Canada, prescription drugs have been developed and made available to treat a wide variety of illnesses, from infections to heart disease and so on. Records of prescription drug fulfillment at coarse Canadian geographic scales were obtained from Health Canada in order to track the use of these drugs by the Canadian population. The obtained prescription drug fulfillment records were in a variety of inconsistent formats, including a large selection of years for which only paper tabular records were available (hard copies). In this work, we organize, digitize, proof and synthesize the full available data set of prescription drug records, from paper to final database. Extensive quality control was performed on the data before use. This data was then analyzed for temporal and spatial changes in prescription drug use across Canada from 1990-2013. In addition, one of major research areas in environmental epidemiological studies is the study of population health risk associated with exposure to ambient air pollution. Prescription drugs can moderate public health risk, by reducing the drug user's physiological symptoms and preventing acute health effects (e.g., strokes, heart attacks, etc.). The cleaned prescription drug data was considered in the context of a common model to examine its influence on the association between air pollution exposure and various health outcomes. Since, prescription drug data were available only at the provincial level, a Bayesian hierarchical model was employed to include the prescription drugs as a covariate at regional level, which were then combined to estimate the association at national level. Although further investigations are required, the study results suggest that the prescription drugs influenced the air pollution related public health risk. Author Keywords: Data, Error checking, Population health, Prescriptions
Capital Ratios and Liquidity Creation
Using quarterly data from the six largest Canadian banks, we investigate the relationship between regulatory capital ratio and on-balance sheet liquidity created in the Canadian economy by “Big Six”. We find a significant positive relationship between Tier 1 capital ratio and on-balance sheet liquidity creation for Canadian big six banks, implying that large banks in Canada favor risks and rely on capital to fund illiquid assets. In contrast, for smaller banks, the relationship is significantly negative. Our results are robust to dynamic panel regression using 2-Step GMM, two exogenous shocks - COVID-19 crisis and the Global Financial Crisis (2007-2009), mergers & acquisitions activities in the banking industry, and core deposits financing. The COVID-19 pandemic and core deposits adversely impact the Tier 1 capital ratio’s relationship with on-balance-sheet liquidity creation, while the global financial crisis (2007-2009) effect on the association is insignificant. Author Keywords: Big Six, COVID -19, Deposits, Liquidity Creation, Tier 1 Capital Ratio,
Assessing the Cost of Reproduction between Male and Female Sex Functions in Hermaphroditic Plants
The cost of reproduction refers to the use of resources for the production of offspring that decreases the availability of resources for future reproductive events and other biological processes. Models of sex-allocation provide insights into optimal patterns of resource investment in male and female sex functions and have been extended to include other components of the life history, enabling assessment of the costs of reproduction. These models have shown that, in general, costs of reproduction through female function should usually exceed costs through male function. However, those previous models only considered allocations from a single pool of shared resources. Recent studies have indicated that the type of resource currency can differ for female and male sex functions, and that this might affect costs of reproduction via effects on other components of the life history. Using multiple invasibility analysis, this study examined resource allocation to male and female sex functions, while simultaneously considering allocations to survival and growth. Allocation patterns were modelled using both shared and separate resource pools. Under shared resources, allocation patterns to male and female sex function followed the results of earlier models. When resource pools were separate, however, allocations to male function often exceeded allocations to female function, even if fitness gains increased less strongly with investment in male function than with investment in female function. These results demonstrate that the costs of reproduction are affected by (1) the types of resources needed for reproduction via female or male function and (2) via trade-offs with other components of the life history. Future studies of the costs of reproduction should examine whether allocations to reproduction via female versus male function usually entail the use of different types of resources. Author Keywords: Cost of Reproduction, Gain Curve, Life History, Resource Allocation Patterns, Resource Currencies
Modelling Depressive Symptoms in Emerging Adulthood
Depression during the transition into adulthood is a growing mental health concern, with overwhelming evidence linking the developmental risk for depressive symptoms with maternal depression. In addition, there is a lack of research on the protective role of socioemotional competencies in this context. This study examines independent and joint effects of maternal depression and trait emotional intelligence (TEI) on the longitudinal trajectory of depressive symptoms during emerging adulthood. A series of latent growth models was applied to three biennial cycles of data from a nationally representative sample (N=933) from the Canadian National Longitudinal Survey of Children and Youth. We assessed the trajectory of self-reported depressive symptoms from age 20 to 24 years, as well as whether it was moderated by maternal depression at age 10 to 11 and TEI at age 20, separately by gender. The results indicated that mean levels of depression declined during the emerging adulthood in females, but remained relatively stable in males. Maternal depressive symptoms significantly positively predicted depressive symptoms across the entire emerging adulthood in females, but only at age 20-21 for males. In addition, likelihood of developing depressive symptoms was attenuated by higher global TEI in both females and males, and additionally by higher interpersonal skills in males. Our findings suggest that interventions for depressive symptoms in emerging adulthood should consider development of socioemotional competencies. Author Keywords: Depression, Depressive Symptoms, Emerging Adulthood, Intergenerational Risk, Longitudinal, Trait Emotional Intelligence
Academic Efficiency
Universities produce a significant and increasing share of basic research that is later commercialized by firms. We argue that the university's prominence as a producer of basic research is the result of a differential efficiency in research production that cannot be replicated by firms or individual agents - teaching. By using research accomplishments to signal knowledge and attract tuition-paying students, universities are uniquely positioned to undertake certain types of research projects. However, in a market for innovation without patent rights, a significant and increasing number of basic research projects, that are social welfare improving, cannot be initiated by firms or universities. The extension of patent rights to university-generated research elegantly redresses this issue and leaves us to ponder important questions about the future of our innovation-driven economies. Author Keywords: Innovation, Intellectual Property Rights, Research, Science Technology and Innovation Policy
Sinc-Collocation Difference Methods for Solving the Gross-Pitaevskii Equation
The time-dependent Gross-Pitaevskii Equation, describing the movement of parti- cles in quantum mechanics, may not be solved analytically due to its inherent non- linearity. Hence numerical methods are of importance to approximate the solution. This study develops a discrete scheme in time and space to simulate the solution defined in a finite domain by using the Crank-Nicolson difference method and Sinc Collocation Methods (SCM), respectively. In theory and practice, the time discretiz- ing system decays errors in the second-order of accuracy, and SCMs are decaying errors exponentially. A new SCM with a unique boundary treatment is proposed and compared with the original SCM and other similar numerical techniques in time costs and numerical errors. As a result, the new SCM decays errors faster than the original one. Also, to attain the same accuracy, the new SCM interpolates fewer nodes than the original SCM, which saves computational costs. The new SCM is capable of approximating partial differential equations under different boundary con- ditions, which can be extensively applied in fitting theory. Author Keywords: Crank-Nicolson difference method, Gross-Pitaevskii Equation, Sinc-Collocation methods
Combinatorial Collisions in Database Matching
Databases containing information such as location points, web searches and fi- nancial transactions are becoming the new normal as technology advances. Conse- quentially, searches and cross-referencing in big data are becoming a common prob- lem as computing and statistical analysis increasingly allow for the contents of such databases to be analyzed and dredged for data. Searches through big data are fre- quently done without a hypothesis formulated before hand, and as these databases grow and become more complex, the room for error also increases. Regardless of how these searches are framed, the data they collect may lead to false convictions. DNA databases may be of particular interest, since DNA is often viewed as significant evi- dence, however, such evidence is sometimes not interpreted in a proper manner in the court room. In this thesis, we present and validate a framework for investigating var- ious collisions within databases using Monte Carlo Simulations, with examples from DNA. We also discuss how DNA evidence may be wrongly portrayed in the court room, and the explanation behind this. We then outline the problem which may occur when numerous types of databases are searched for suspects, and framework to address these problems. Author Keywords: big data analysis, collisions, database searches, DNA databases, monte carlo simulation
Influence of geodemographic factors on electricity consumption and forecasting models
The residential sector is a major consumer of electricity, and its demand will rise by 65 percent by the end of 2050. The electricity consumption of a household is determined by various factors, e.g. house size, socio-economic status of the family, size of the family, etc. Previous studies have only identified a limited number of socio-economic and dwelling factors. In this thesis, we study the significance of 826 geodemographic factors on electricity consumption for 4917 homes in the City of London. Geodemographic factors cover a wide array of categories e.g. social, economic, dwelling, family structure, health, education, finance, occupation, and transport. Using Spearman correlation, we have identified 354 factors that are strongly correlated with electricity consumption. We also examine the impact of using geodemographic factors in designing forecasting models. In particular, we develop an encoder-decoder LSTM model which shows improved accuracy with geodemographic factors. We believe that our study will help energy companies design better energy management strategies. Author Keywords: Electricity forecasting, Encoder-decoder model, Geodemographic factors, Socio-economic factors

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Graduate student theses produced at Trent University. You may also browse theses and dissertations by year, program, or author.

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